INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Forest fire prediction is the use of different methods and tools to estimate the risk and severity of a fire in a forest area. Some methods used in forest fire prediction are statistical analysis, machine learning algorithms, and remote sensing techniques.
Forest fire prediction models can be used to provide early warning systems to alert authorities and residents of potential fire danger. These models also help to identify areas that are at high risk of fires and enable authorities to take preventive actions, such as enforcing fire bans and evacuation orders, to reduce or minimize the impact of forest fires.
In the future, predicting forest fire is expected to reduce the impact of fire. In this project, we are developing a forest fire prediction system that predicts the probability of catching fire using meteorological parameters like location, temperature, and more.
We use Random Forest regression algorithm to implement this system.
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Cite Article:
"Machine Learning Techniques for Estimating Forest Fire Risk and Severity", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.a292-a295, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404038.pdf
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2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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